1. Field of the Invention
The present invention relates generally to the field of video signal processing and noise estimation.
2. Description of the Related Art
Removing noise from a video signal either before or after performing video processing functions (i.e. de-interlacing, edge enhancement, scaling, etc.) may improve video quality. However, noise removal often has the effect of either softening the image by attenuating the spatial details of the signal, or introducing ghosting artifacts. Therefore, it is important to avoid unnecessary noise filtering in order to maintain the sharpness of detail in the video signal.
Before noise is removed, an estimate of the noise existent in the signal is necessary in order to remove the proper frequencies. There are several ways to estimate noise and to differentiate between noise and the details of the video signal, including block based methods. Block based methods of noise estimation attempt to locate regions in the signal with the least amount of signal variation. Variances calculated on the homogenous regions or blocks are considered in the computation of noise in the signal. However, if the block evaluated is only a small portion of the total signal, the calculated noise may not be representative of the entire signal. Additionally, the implementation of a wavelet based noise estimation approach may be computationally complex and require extra hardware.
A block based noise estimator, specifically adapted for Gaussian noise in video, and tunable to adapt to lower noise power situations may have simpler computational complexity than other noise estimators, may be more effective than a simple noise estimator, and may overcome some of the difficulties typical when implementing a traditional block based noise estimator.